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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xls-r-300m-phoneme-timit |
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results: [] |
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datasets: |
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- timit_asr |
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language: |
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- en |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# working |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3630 |
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- Wer: 0.6243 |
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- Cer: 0.1316 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2000 |
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- training_steps: 10000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:------:|:-----:|:---------------:|:------:|:------:| |
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| 3.5325 | 11.9 | 1000 | 3.4897 | 1.0 | 0.9266 | |
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| 2.1973 | 23.81 | 2000 | 1.1350 | 0.8396 | 0.2403 | |
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| 1.4762 | 35.71 | 3000 | 0.5270 | 0.6845 | 0.1563 | |
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| 1.2409 | 47.62 | 4000 | 0.4195 | 0.6331 | 0.1403 | |
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| 1.1241 | 59.52 | 5000 | 0.3845 | 0.6362 | 0.1379 | |
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| 1.024 | 71.43 | 6000 | 0.3716 | 0.6321 | 0.1355 | |
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| 0.9922 | 83.33 | 7000 | 0.3728 | 0.6290 | 0.1331 | |
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| 0.9432 | 95.24 | 8000 | 0.3648 | 0.6170 | 0.1321 | |
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| 0.9279 | 107.14 | 9000 | 0.3643 | 0.6248 | 0.1325 | |
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| 0.9268 | 119.05 | 10000 | 0.3630 | 0.6243 | 0.1316 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
